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PROCEDIA
2010
157views more  PROCEDIA 2010»
13 years 3 months ago
Recommender system for predicting student performance
Recommender systems are widely used in many areas, especially in e-commerce. Recently, they are also applied in e-learning tasks such as recommending resources (e.g. papers, books...
Nguyen Thai-Nghe, Lucas Drumond, Artus Krohn-Grimb...
AIED
2007
Springer
13 years 11 months ago
Predicting Students' Performance with SimStudent: Learning Cognitive Skills from Observation
SimStudent is a machine-learning agent that learns cognitive skills by demonstration. SimStudent was originally built as a building block for Cognitive Tutor Authoring Tools to hel...
Noboru Matsuda, William W. Cohen, Jonathan Sewall,...
UM
2007
Springer
13 years 11 months ago
The Effect of Model Granularity on Student Performance Prediction Using Bayesian Networks
A standing question in the field of Intelligent Tutoring Systems and User Modeling in general is what is the appropriate level of model granularity (how many skills to model) and h...
Zachary A. Pardos, Neil T. Heffernan, Brigham Ande...
EDM
2010
309views Data Mining» more  EDM 2010»
13 years 6 months ago
A Case Study: Data Mining Applied to Student Enrollment
One of the main problems faced by university students is deciding the right learning path based on available information such as courses, schedules and professors. In this context,...
César Vialardi Sacín, Jorge Chue, Al...
ICDE
2007
IEEE
110views Database» more  ICDE 2007»
13 years 11 months ago
Embedding Emotional Context in Recommender Systems
Emotional context is becoming a promising paradigm to develop more intuitive and sensitive recommender systems. Ambient Recommender Systems, arise from the analysis of new trends ...
Gustavo González, Josep Lluís de la ...